(1) Field of the Invention
The present invention relates generally to the field of estimation and tracking, and more particularly to target motion analysis (TMA) suitable for Naval applications.
(2) Description of the Prior Art
As is well known, a fundamental property of bearings-only target motion analysis (TMA) is that the contact range is not observable prior to an ownship maneuver. Hence, for a single-leg of ownship motion (a leg is defined as a time interval of constant platform velocity) only a partial solution is achievable. This introduces a time-latency in the estimation process owing to the necessity of collecting sufficient data during multiple ownship legs. This time-delay may be unacceptable under conditions when rapid estimates are desired, albeit of poorer quality, to facilitate a quick tactical response (such as in the close-aboard contact situation). As such, methods for deriving meaningful TMA solutions during single leg tactical encounters are of primary interest.
One presently utilized method for bearings-only target motion analysis for underwater target tracking is known as the parameter evaluation plot (PEP), which is a grid-search technique that is discussed in more detail hereinafter. In recent years, the PEP has been integrated into the TMA functionality of the U.S. Navy's newer Combat Systems. The accuracy of the PEP solution is a function of a range-grid resolution. With finer samples, search space resolution is improved; and the closer the estimated minimum-cost track will be to the desired true solution. However, the cost function evaluation used in the PEP becomes computationally demanding if the number of search-space samples becomes too large, impacting real-time system performance. Thus, there is an inherent tradeoff between solution accuracy and computational complexity when employing the uniform grid technique used in the PEP.
Previous efforts to related problems are described by the following patents:
U.S. Pat. No. 5,067,096, issued Nov. 19, 1991, to Olson et al., discloses a target engagement system that uses target motion analysis to determine a target engagement decision for ground targets, such as vehicles. The input to the engagement system is the target azimuth as a function of time. A detect algorithm issues and records a detect azimuth when confirmation is made that a valid target is being tracked and legitimate azimuth information is being provided. The engagement algorithm then begins and records the time intervals it takes for the target to cross two sectors, each covering 20 degrees and separate by 10 degrees. Thus, first time interval is measured from detect azimuth to 20 degrees after detect azimuth, and the second time interval is measured from 30 degrees after detect azimuth to 50 degrees after detect azimuth. When the first and second time intervals have been recorded, the ratio of the first time interval to the second time interval is calculated. If this ratio is greater than 2.0, then the target is estimated to be within range and is subsequently attacked. Otherwise, the target is greater than the range and no action is taken.
U.S. Pat. No. 5,432,753, issued Jul. 11, 1995, to Brian H. Maranda, discloses a system for target detection and localization with an algorithm for performing target motion analysis (TMA) using data from a passive sonar array and which works directly with beam spectra to estimate the target track. The system determines when the coordinate trajectory of a hypothesized target aligns with the coordinate trajectory of an actual target and operates by forming long-term integrated spectral values from short-term values of frequency and angle coordinate values. The hypothesized target track that yields the maximum long-term integrated spectral value is used as the estimate of the true target track. A track generator is used to generate hypothesized target tracks for a search grid in the form of vectors that are clocked downward in a chain of latches. The latches are connected through computational elements, which are supplied with non-acoustic data, and RAMs to a summation pipeline, the RAMs being supplied with data from an array's sonar processor. The computational elements compute and provide angle and frequency addresses to the RAMs whose outputs are applied to adders in the summation pipeline. Each RAM holds data for a single two-dimensional FRAZ spectrum. The summation pipeline supplies a completed sum of short-term spectral values at its output to provide the required long-term integrated spectral values.
U.S. Pat. No. 5,471,433, issued Nov. 28, 1995, to Hammell et al., discloses a trajectory estimation system for estimating a trajectory of a target in response to a series of data items which are generated in response to motion of the target. The trajectory estimation system includes a data segmentation means and a trajectory selection means. The data segmentation means processes the series of data items in accordance with a regression/multiple-hypothesis methodology to generate a plurality of segments, each having associated data items, which have similar features. The trajectory selection means for processing said segments in accordance with a multiple-model hypothesis methodology to generate a corresponding statistically-supportable candidate trajectory motion estimate of target motion thereby to provide indicia of an overall trajectory of the target.
U.S. Pat. No. 5,506,817, issued Apr. 9, 1996, to Francis J. O'Brien, Jr., discloses an adaptive statistical filter system for receiving a data stream, which comprises a series of data values from a sensor associated with successive points in time. Each data value includes a data component representative of the motion of a target and a noise component, with the noise components of data values associated with proximate points in time being correlated. The adaptive statistical filter system includes a prewhitener, a plurality of statistical filters of different orders, stochastic decorrelator and a selector. The prewhitener generates a corrected data stream comprising corrected data values, each including a data component and a time-correlated noise component. The plural statistical filters receive the corrected data stream and generate coefficient values to fit the corrected data stream to a polynomial of corresponding order and fit values representative of the degree of fit of corrected data stream to the polynomial. The stochastic decorrelator uses a spatial Poisson process statistical significance test to determine whether the fit values are correlated. If the test indicates the fit values are not randomly distributed, it generates decorrelated fit values using an autoregressive moving average methodology, which assesses the noise components of the statistical filter. The selector receives the decorrelated fit values and coefficient values from the plural statistical filters and selects coefficient values from one of the filters in response to the decorrelated fit values. The coefficient values are coupled to a target motion analysis module, which determines position and velocity of a target.
U.S. Pat. No. 5,732,043, issued Mar. 24, 1998, to Nguyen et al., discloses a method for selecting a set of four target bearings from a plurality of bearing measurements to optimize rapidity, accuracy and stability of a target track solution in a bearings-only target motion algorithm. Four bearings are selected to generate the deterministic solution by first selecting a candidate bearing set, then computing a set of “n” solutions from the candidate set and others adjacent thereto. Motion parameters are then computed, and any solution exhibiting parameters outside a user-defined deviation from the mean is discarded. The mean target parameters of the remaining solutions may again be computed, and further culling out performed, until the desired distribution is achieved. An optimal solution is chosen as the solution from the remaining sample space that is closest to the mean in target range, course and speed. The other solutions in the remaining solution sample space may be displayed to an operator in the form of a scatter plot of all solutions, or by a range envelope encompassing the extent of solution ranges.
U.S. Pat. No. 5,877,998, issued Mar. 2, 1999, to Aidala et al., discloses a method for estimating the motion of a target relative to an observer station and a system for performing the method. The method includes the steps of: generating data representative of the motion of the target relative to the observer station during first, second, and subsequent measurement legs; processing the data to yield smoothed estimate of the bearing, bearing rate, and bearing acceleration of the target during each measurement leg; and processing the smoothed estimates of the bearing, bearing rate, and bearing acceleration of the target to provide an estimate of the position of the target relative to the observer station and the velocity of the target. The system for performing the method includes a data preprocessing subsystem for generating the smoothed estimate of the bearing rate, bearing and bearing acceleration, a passive localization and target motion analysis subsystem, and a trajectory modeling subsystem having a first module for creating a model of the observer station motion and a second module for creating a model of the motion of the target.
The above patents do not utilize the PEP techniques and do not show how it would be possible to obtain the accuracy of a PEP fine resolution grid without the computational complexity/time required by prior art PEP techniques to produce a fine resolution grid. Consequently, those skilled in the art will appreciate the present invention that addresses the above and other problems.